The present invention relates to a method of constructing a behavior model of an airplane engine, in particular in order to track the operation of the engine.
For example in the context of tracking the starting sequences of an airplane engine, it is necessary to eliminate the influence context (such as temperature, pressure, speed, etc.) from the indicators of degradation (e.g. such as the duration of starting). In order to do this, an estimate is constructed of the value of the indicator in the non-degraded state, as a function of the context. This estimate is then subtracted from the measured value of the indicator. The result that is obtained is representative of the state of degradation of the system under study.
With a sound engine, the estimate of the indicator is constructed by means of a behavior model. This model is itself obtained by statistical regression of a reference database representative of the sound state of the engine. The size of this database has a strong influence on the quality of the training of the regression function. The larger the database and the greater the number of different contexts that it contains, the wider the range over which the trained function is valid.
In the prior art, the regression function is trained either from a generic database containing data about a fleet comprising a plurality of engines, or else from a specific database containing only data that is specific to the engine under study.
Nevertheless, both of those methods present drawbacks.
When a generic behavior model is constructed from a database concerning a plurality of engines, the model does not take account of differences between engines, such as manufacturing disparities. The model is therefore relatively inaccurate, giving rise to regression of poor performance. Nevertheless, the advantage of that model is that its large training database makes it robust when faced with contexts that are rare, and it therefore provides a range of validity that is broad.
When a specific behavior model is constructed from a database specific to one engine, the model does not benefit from data about other engines, and it is therefore constructed on a database that is not so rich and that covers fewer possible situations. It is therefore not very robust when faced with contexts that are rare, which leads to a narrower range of validity. Furthermore, the database specific to each engine is limited by the duration over which the engine has been tracked.